Center for Computational and Theoretical Biology

BSc/MSc projects

We always offer undergraduate projects and theses (BSc/MSc) in biosciences, neurosciences, biochemistry and (via collaborations) in physics and computer science. The topic can be adapted to your prior knowledge, but some experience with image analysis is helpful, e.g from one of our courses.

If you are a BSc/MSc student and interested in doing a project with us, please contact Philip Kollmannsberger.­­

Open Topics:

  • Density-based clustering and classification of dSTORM data
  • Deep Learning for denoising, segmentation and tracking
  • Simulations of spatial network development
  • Analysis of mitotic figures in fluorescence images
  • Denoising and de-wedging of electron tomograms with neural networks
  • Benchmarking and optimization of skeletonization algorithms

You can also bring your own idea, collaborate with an experimental group, or tackle a public challenge, e.g. from here:

Ongoing Projects:


M.Sc. Thesis Tracking immune cell activity in-vivo with CNNs Tristan Beste with Prof. Florian Erhard, Virology
M.Sc. Project Deep Learning for denoising of electron tomograms Helmut Becker  
B.Sc. Project Fiji plugins to analyze microscopy images of T.brucei Tuguldur Tumurbaatar with Dr. Brooke Morriswood, ZEB
M.Sc. Project Neural Network to classify autocorrelation in dSTORM images Julius Körber  
M.Sc. Project Automating connectomics of the C.elegans Dauer larva Felix Fink with Prof. Christian Stigloher, ICF
external Quantification of tissue growth from time-lapse PhC movies Tassilo v. Trotha Supervisor: Mario Benn, ETH



M.Sc. Project Automated quantification of axon demyelination in EM images Jan Hoffmann Lab Rotation Transl. Neurosci.
M.Sc. Project Bird recognition with Tensorflow on a Raspberry Pi Sarah Franz  
M.Sc. Project Deep Learning based measurement of wild bee mandibles Lucas Fortune with Dr. Samuel Boff, Zoo-3
M.Sc. Project AI-based detection of synaptic vesicles Lukas Baltes  
M.Sc. Thesis Reproducible workflow for fMRI-based MDD biomarkers Martin Hochheimer with Prof. Hewig, Psychology
M.Sc. Project Quality assessment of Deep Learning CLEM registration Rick Seifert  


M.Sc. Thesis Applying a U-Net to segment microtubules of T.brucei Johannes Schmidt with Markus Engstler, ZEB
M.Sc. Thesis Segmentation of Insect Brain Images Using Deep Neural Networks Nico Braun with Prof. Keram Pfeiffer, Zoo-2
M.Sc. Thesis Optimization of Localization Microscopy with Deep Learning Andreas Berberich with Prof. Markus Sauer and Prof. Karl Mannheim
M.Sc. Thesis MR-Imaging of Neurovascular Coupling of the PNS Christopher Nauroth with Prof. Mirko Pham, Neuroradiology
M.Sc. Project Automated cell tracking with U-Net and DeepImageJ Tristan Beste with Dr. Kathrin Stelzner, Microbiology


B.Sc. Thesis Correlation of Light- and Electron microscopic images using deep neural networks Rick Seifert with Prof. Christian Stigloher, ICF
B.Sc. Thesis Automated analysis of cell-cell interactions in in-vivo confocal microscopy Julia Homer with Prof. Florian Erhard, Virology
M.Sc. Thesis Annotation of Cryo-EM density maps with convolutional neural networks Philipp Mostosi with Dr. Andrea Thorn, Biochemistry
M.Sc. Project Tracing of microtubules in electron tomograms of T.brucei Johannes Schmidt with Prof. Markus Engstler, ZEB
M.Sc. Project Live tracking of honey bees for behavioral experiments Lucas Fortune with Prof. Ricarda Scheiner, Zoo-2
M.Sc. Project Benchmarking of unsupervised denoising algorithms Nico Braun  

2018 and earlier

M.Sc. Thesis Machine Learning for segmentation of 3D EM images Maria Theiss  
B.Sc. Thesis Automated pollen classification with deep learning Kilian Maidhof with Dr. Alexander Keller, CCTB
M.Sc. Project Fiji Macro for automated vesicle segmentation in anisotropic EM images Yannic Lurz  
M.Sc. Project Analyzing filopodia expression in fluorescent images of HEK cells Martin Hochheimer Translational Neuroscience
M.Sc. Project GPU-optimized true non-local means denoising Philipp Mostosi  
B.Sc. Project Pixelwise identification of microtubules in electron tomograms of T.brucei Johannes Schmidt  
B.Sc. Project Comparison of classical and trainable segmentation for fluorescence images Mario Schneider  

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